Early detection of cancer via screening has been shown to lead to improved survival for several common malignancies. However, screening comes with significant risks and expenses. One important issue faced by all screening tests is detecting as many cancers as possible while minimizing identification of false positives. False positive screening results induce anxiety in patients and their families, require additional expensive tests, and may result in harm if a follow-up study leads to a complication. We propose to develop a novel, genomic approach for cancer screening that leverages insights gained from high throughput re-sequencing of cancer genomes. We will develop this method in the context of lung cancer, since it is the number one cause of cancer deaths and since low dose computed tomography (CT) screening has recently been shown to produce significant survival benefits in high-risk patients. However, ~95% of positive screening results from low dose CT lung cancer screenings are false positives and so improvements are clearly needed. This proposal describes our plan to develop, optimize, and test our method. We will perform both pre-clinical and clinical evaluations and will test our approach in multiple settings, includig as a secondary screening procedure for differentiating between true positive and false positive screening results and as a primary screening modality. Importantly, the method is readily extendable to any cancer for which high throughout sequencing data are available and we envision ultimately being able to screen for most common cancers using a single assay.